Companies, including those in the online gaming industry, like https://www.playamo.com/en-CA, must navigate risks when adopting new technologies like artificial intelligence (AI). While some risks are common to any new tech deployment, AI brings unique challenges. Executives must use best practices to align AI with business goals. They must also develop expertise and manage change.
Trust Issues Can Halt AI Progress
Not all workers are ready to embrace AI.
Professional services firm KPMG, in a partnership with the University of Queensland in Australia, found that 61% of respondents to its “Trust in Artificial Intelligence: Global Insights 2023″ report are either ambivalent about or unwilling to trust AI.
Experts say an AI implementation will only be productive with that trust.
Consider, for example, what would happen if workers don’t trust an AI solution. This solution is on a factory floor. It determines a machine must be shut down for maintenance. Even if the AI system is always accurate, if the user doesn’t trust the machine, then that AI is a failure.
AI can have Unintentional Biases.
AI uses significant amounts of data to learn and make decisions. AI can make wrong decisions if the data is unfair or has problems. For example, a report says that in New York City, Black and Latino people were stopped by police much more than White people. So, if AI uses this police data, it might wrongly think these neighborhoods have more crime. This shows AI can be unfair if it learns from biased data.
Biases, Errors Magnified by the Volume of AI Transactions
Human workers have biases and make mistakes. Yet, the consequences of their errors are limited to the volume of work they do before they are caught. This is often a little. However, the consequences of biases or hidden errors in operational AI systems can be exponentially more significant.
As experts explained, humans might make dozens of mistakes in a day. A bot is handling millions of transactions daily magnifies any single error by millions.
AI Can Create Unexplainable Results, Thereby Damaging the Trust
Explainability means being able to understand how AI makes its decisions. It’s important because it helps people trust AI. But sometimes, it’s hard to explain its decisions. This is especially true with complex AI that learns independently. This can make people hesitant to use AI, even though it has many benefits. A McKinsey article said that for AI to be used widely. Everyone must trust that it’s making fair and accurate decisions. Users who need help understanding how AI works might not use it.
AI Can Have Unintended Consequences
Similarly, using AI can have consequences that enterprise leaders either fail to consider or are unable to contemplate, Wong said.
A 2022 White House report mentioned a study by Google. This study found that AI often misunderstands talks about disabilities and mental health, treating even positive statements like “I will fight for people with mental illness” as unfavorable. This shows AI can be biased in how it reads our words.
Liability Issues Are Unsettled and Undetermined
Big questions arise about who is responsible when AI makes mistakes. This applies to decisions and products. It’s not clear yet who should be blamed for any problems caused by AI.
For example, FTI Consulting’s Kelly said it needs to be clarified who — or what — would or should be faulted if AI writes a lousy piece of computer code that causes problems. That issue leaves executives, lawyers, courts, and lawmakers to move forward with highly uncertain AI use cases.
AI Use vs. Future Laws: A Tightrope Walk
Governments worldwide are considering whether to put laws in place to regulate the use of AI. They are also considering what those laws should be. Legal and AI experts expect governments to pass new rules in the coming years.
Organizations might then need to adjust their AI roadmaps, curtail their planned implementations, or even cut some of their AI uses if they run afoul of any forthcoming legislation, Kelly said.
She added that executives could find that challenging. AI is often embedded in the technologies and services they buy from vendors. This means enterprise leaders must review their developed AI initiatives. They must also review the AI in the products and services purchased from others. This is to ensure they’re not breaking any laws.
AI Might Erode Critical Skills
After two Boeing 737 Max plane crashes, experts worry that pilots lose basic flying skills. This is because of too much automation. They fear AI might make us forget how to do tasks without technology. Yossi Sheffi, a supply chain expert, warns to stop valuing people who can work without tech.
How to Manage Risks
To manage AI risks, organizations must understand them and implement policies for quality data, testing, and ongoing monitoring. They should have frameworks for ethical results involving the board and C-suite. All executives need to be part of the solution, not IT.
